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A Systems Engineering Approach to Electro-Mechanical Actuator Diagnostic and Prognostic Development

Metadata Updated: December 6, 2023

The authors have formulated a Comprehensive Systems Engineering approach to Electro-Mechanical Actuator (EMA) Prognostics and Health Management (PHM) system development. The approach implements software tools to integrate simulation-based design principles and dynamic failure mode and effects analysis. It also provides automated failure mode insertion and propagation analysis, PHM algorithm design and verification, full dynamic simulations, code generation, and validation testing. This process aims to produce the appropriate fault detection and prediction algorithms needed for successful development of an EMA PHM system.

As an initial use case, the developed approach was implemented to develop and validate a model-based, virtual sensor software package for landing gear EMA PHM. This effort included creation of a dynamic, component-level system model that can be used to virtually sense parameters, detect degradation, isolate probable root cause, and assess severity. This model is also used as a virtual test bed for performing fault insertion analysis to address algorithm development and experimental prioritization. The developed model was validated using data from a test stand, which was specifically constructed for EMA PHM development. The model-based predictor was then coupled with failure mode diagnostics, advanced knowledge fusion, and failure mode progression algorithms to form a complete prototype EMA PHM solution.

Reproduced by kind permission of MFPT (www.mfpt.org).

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date November 12, 2020
Metadata Updated Date December 6, 2023
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date December 6, 2023
Publisher Dashlink
Maintainer
Identifier DASHLINK_392
Data First Published 2011-06-07
Data Last Modified 2020-01-29
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 602765b2-3ed2-4c09-9b5d-75d878af2b28
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://c3.nasa.gov/dashlink/resources/392/
Program Code 026:029
Source Datajson Identifier True
Source Hash d2bdf24efe2037645fdb19db82c0fa0f22453e412605510868829b9c666145a0
Source Schema Version 1.1

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